Computational cardiac physiology for new modelers: Origins, foundations, and futureShow others and affiliations
2022 (English)In: Acta Physiologica, ISSN 1748-1708, E-ISSN 1748-1716, Vol. 236, no 2, article id e13865Article, review/survey (Refereed) Published
Abstract [en]
Mathematical models of the cardiovascular system have come a long way since they were first introduced in the early 19th century. Driven by a rapid development of experimental techniques, numerical methods, and computer hardware, detailed models that describe physical scales from the molecular level up to organs and organ systems have been derived and used for physiological research. Mathematical and computational models can be seen as condensed and quantitative formulations of extensive physiological knowledge and are used for formulating and testing hypotheses, interpreting and directing experimental research, and have contributed substantially to our understanding of cardiovascular physiology. However, in spite of the strengths of mathematics to precisely describe complex relationships and the obvious need for the mathematical and computational models to be informed by experimental data, there still exist considerable barriers between experimental and computational physiological research. In this review, we present a historical overview of the development of mathematical and computational models in cardiovascular physiology, including the current state of the art. We further argue why a tighter integration is needed between experimental and computational scientists in physiology, and point out important obstacles and challenges that must be overcome in order to fully realize the synergy of experimental and computational physiological research.
Place, publisher, year, edition, pages
Wiley , 2022. Vol. 236, no 2, article id e13865
Keywords [en]
cardiovascular physiology, computer models, mathematical modeling
National Category
Other Mathematics Cardiology and Cardiovascular Disease
Identifiers
URN: urn:nbn:se:kth:diva-329157DOI: 10.1111/apha.13865ISI: 000844163200001PubMedID: 35959512Scopus ID: 2-s2.0-85136556268OAI: oai:DiVA.org:kth-329157DiVA, id: diva2:1768628
Note
QC 20230614
2023-06-152023-06-152025-02-10Bibliographically approved